Quality standards and guardrails

Problem

As more contributors add semantic detectors, profile statistics, and inspector template sections, there are no enforced standards for what constitutes acceptable output quality. A new detector might be added with no confidence threshold, producing low-quality type labels that pollute the profile. A new template section might render inconsistently across themes, or omit null-state handling. Without defined quality standards — covering semantic detection accuracy thresholds, confidence minimums for display, template rendering requirements, and test coverage expectations — the inspector experience will degrade as the contributor base grows, producing inconsistent and unreliable profiles that undermine analyst trust.

Context

• Teams are judging readiness for warehouse profiling, semantic inference, and analyst-facing inspect/context artifacts inconsistently because there is no single quality bar that covers correctness, UX clarity, failure handling, and maintenance expectations.
• Without explicit standards, work gets approved on local intuition and later re-opened when another reviewer finds a gap that was never written down.
• Expected touchpoints include dataface/core/inspect/, schema-context consumers, inspect docs, and core tests, review checklists, docs, and any eval or QA surfaces used to prove a change is safe to ship.

Possible Solutions

• A - Rely on experienced reviewers to enforce quality informally: flexible, but it does not scale and leaves decisions hard to reproduce.
• B - Recommended: define a concise quality rubric plus guardrails: specify acceptance criteria, required evidence, and clear anti-goals so reviews are consistent.
• C - Block all new work until a comprehensive handbook exists: safer in theory, but too heavy for the milestone and likely to stall momentum.

Plan

1. List the failure modes and review disagreements that matter most for warehouse profiling, semantic inference, and analyst-facing inspect/context artifacts, using recent work as concrete examples.
2. Turn those into a small set of quality standards, required validation evidence, and explicit guardrails for unsupported or risky cases.
3. Update the relevant docs, task/checklist expectations, and test or QA hooks so the standards are actually enforced.
4. Use the rubric on a representative set of recent or in-flight items and tighten the wording anywhere it still leaves too much ambiguity.

Implementation Progress

Review Feedback

• [ ] Review cleared